Method and apparatus with fingerprint verification

ABSTRACT

A fingerprint verification method and apparatus is disclosed. The fingerprint verification method may include obtaining an input fingerprint image, determining a matching region between the input fingerprint image and a registered fingerprint image, determining a similarity corresponding to the matching region, representing a determined indication of similarities between the input fingerprint image and the registered fingerprint image, relating the determined similarity to the matching region as represented in a matching region-based similarity, determining a result of a verification of the input fingerprint image based on the matching region-based similarity, and indicating the result of the verification.

CROSS-REFERENCE TO RELATED APPLICATION(S)

This application claims the benefit under 35 USC § 119(a) of KoreanPatent Application No. 10-2017-0031889 filed on Mar. 14, 2017 and KoreanPatent Application No. 10-2017-0097033 filed on Jul. 31, 2017 in theKorean Intellectual Property Office, the entire disclosures of which areincorporated herein by reference for all purposes.

BACKGROUND 1. Field

The following description relates to fingerprint verificationtechnology.

2. Description of Related Art

Automated biometrics-based verification technologies may be used toverify a user, for example, through analyses of a fingerprint, an iris,a voice, a face, and/or blood vessels. Such biological characteristicsused for user authentication differ from individual to individual,rarely change during a user's lifetime, and have a low risk of beingstolen or copied. In addition, because individuals always carry suchcharacteristic information, the individuals do not need to remember toor intentionally carry any corresponding identification materials, andthus may not suffer an inconvenience when performing verifications withthe biological characteristics. Currently, fingerprint verificationapproaches has been used for the user authentication, e.g., due to theirhigh level of convenience, security, and economic efficiency.

SUMMARY

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is this Summaryintended to be used as an aid in determining the scope of the claimedsubject matter.

In one general aspect, a processor implemented fingerprint verificationmethod includes obtaining an input fingerprint image, determining amatching region between the input fingerprint image and a registeredfingerprint image, determining a similarity corresponding to thematching region, representing a determined indication of similaritiesbetween the input fingerprint image and the registered fingerprintimage, relating the determined similarity to the matching region asrepresented in a matching region-based similarity, determining a resultof a verification of the input fingerprint image based on the matchingregion-based similarity, and indicating the result of the verification.

The relating of the determined similarity to the matching region asrepresented in the matching region-based similarity may includedetermining the matching region-based similarity based on the matchingregion and the determined similarity.

The method may further include generating the matching region-basedsimilarity to include default similarity values and without representinga matching region, where the determining of the matching region-basedsimilarity may include representing the matching region in the matchingregion-based similarity and changing, from the default similarityvalues, similarity values corresponding to the matching regionrepresented in the matching region-based similarity to be the determinedsimilarity.

The determining of the result of the verification may includedetermining a score for the determined matching region-based similarity,and determining whether the verification is successful based on whetherthe score satisfies a predetermined fingerprint verification condition.

The determining of the similarity corresponding to the matching regionmay include determining a first similarity corresponding to a firstmatching region between the input fingerprint image and a firstregistered fingerprint image, the relating of the determined similarityto the matching region as represented in the matching region-basedsimilarity may include determining the matching region-based similaritybased on the first similarity and the first matching region, and, inresponse to a score determined based on the determined matchingregion-based similarity not satisfying a fingerprint verificationcondition, the fingerprint verification method may further includedetermining a second similarity corresponding to a determined secondmatching region between the input fingerprint image and a secondregistered fingerprint image.

The determining of the matching region-based similarity based on thefirst similarity and the first matching region may include allocatingthe first similarity to the first matching region as represented in thedetermined matching region-based similarity.

In response to the score determined based on the determined matchingregion-based similarity not satisfying the fingerprint verificationcondition, the fingerprint verification method may further includeupdating the determined matching region-based similarity based on thesecond matching region and the second similarity.

The updating of the determined matching region-based similarity based onthe second matching region and the second similarity may include, inresponse to an overlapping region being present between the firstmatching region and the second matching region, allocating ormaintaining a greatest similarity between the first similarity and thesecond similarity to the overlapping region as represented in theupdated matching region-based similarity.

The updating of the determined matching region-based similarity based onthe second matching region and the second similarity may further includeallocating the second similarity to a remaining region of the secondmatching region, in which the overlapping region is not reflected, asrepresented in the updated matching region-based similarity.

The determining of the result of the verification may includedetermining a score for the matching region-based similarity, and, inresponse to the score satisfying a predetermined fingerprintverification condition, determining that the verification of the inputfingerprint image is successful.

The determining of the result of the verification may includedetermining whether a total size of one or more matching regions, eachhaving similarities meeting a predetermined threshold value, meets apredetermined threshold size using a matching region-based similarityrepresenting plural matching regions with respect to plural registeredfingerprint images, and determining whether the verification of theinput fingerprint image is successful based on a result of thedetermining of whether the total size meets the predetermined thresholdsize.

The determining of the result of the verification may include, inresponse to an average similarity value, of similarity valuesrespectively related to at least some of plural matching regionsrepresented in a matching region-based similarity with respect to pluralregistered fingerprint images, meeting a predetermined threshold value,determining that the verification of the input fingerprint image issuccessful.

The at least some of the plural matching regions may be less than all ofthe plural matching regions represented in the matching region-basedsimilarity.

The determining of the result of the verification may further include,in response to a score determined based on the matching region-basedsimilarity determined with respect to all registered fingerprint imagesnot satisfying the predetermined fingerprint verification condition,determining that the verification of the input fingerprint image isunsuccessful.

In one general aspect, provided is a non-transitory computer-readablemedium storing instructions, which when executed by a processor, causethe processor to perform one or more or all processes or methodsdescribed herein.

In one general aspect, a processor implemented fingerprint verificationmethod includes obtaining an input fingerprint image, determining afirst similarity corresponding to a first matching region between theinput fingerprint image and a first registered fingerprint image,determining a matching region-based similarity based on the firstsimilarity and the first matching region, determining a score based onthe matching region-based similarity, in response to the score notsatisfying a predetermined fingerprint verification condition,determining a second similarity corresponding to a second matchingregion between the input fingerprint image and a second registeredfingerprint image and updating the matching region-based similaritybased on the second similarity and the second matching region, anddetermining a result of a verification of the input fingerprint imagebased on the matching region-based similarity or the updated matchingregion-based similarity.

The updating of the matching region-based similarity may include, inresponse to an overlapping region being present between the firstmatching region and the second matching region, allocating ormaintaining a greatest similarity between the first similarity and thesecond similarity to the overlapping region represented in the updatedmatching region-based similarity.

The updating of the matching region-based similarity may further includeallocating the second similarity to a remaining region, of the secondmatching region in which the overlapping region is not reflected, asrepresented in the updated the updated matching region-based similarity.

The determining of the result of the verification may includedetermining whether a total size of one or more matching regions, eachhaving a similarity meeting a predetermined threshold value, meets apredetermined threshold size using a matching region-based similarityrepresenting plural matching regions with respect to plural registeredfingerprint images including the first registered fingerprint image andthe second registered fingerprint image, and determining whether theverification of the input fingerprint image is successful based on aresult of the determining of whether the total size meets thepredetermined threshold size.

The determining of the result of the verification may include, inresponse to an similarity average value, of similarity valuesrespectively related to at least some of plural matching regionsrepresented in a matching region-based similarity with respect to pluralregistered fingerprint images including the first registered fingerprintimage and the second registered fingerprint image, meeting apredetermined threshold value, determining that the verification of theinput fingerprint image is successful.

In one general aspect, a processor implemented fingerprint verificationmethod includes obtaining an input fingerprint image, determining afirst matching region between the input fingerprint image and a firstregistered fingerprint image, determining a first similaritycorresponding to the first matching region, determining a matchingregion-based similarity based on the first similarity and the firstmatching region, determining a second matching region between the inputfingerprint image and a second registered fingerprint image, determininga second similarity corresponding to the second matching region,updating the matching region-based similarity based on the secondsimilarity and the second matching region, determining a score based ona finally updated matching region-based similarity representing pluralmatching regions with respect to plural registered fingerprint imagesincluding the first registered fingerprint image and the secondregistered fingerprint image, and determining a result of a verificationof the input fingerprint image based whether on the score meets apredetermined verification condition.

The updating of the matching region-based similarity may include, inresponse to an overlapping region being present between the firstmatching region and the second matching region, allocating ormaintaining a greatest similarity, between the first similaritycorresponding to the first matching region and the second similaritycorresponding to the second matching region, to the overlapping regionrepresented in the updated matching region-based similarity.

The updating of the matching region-based similarity may further includeallocating the second similarity to a remaining region, of the secondmatching region in which the overlapping region is not reflected, asrepresented in the updated matching region-based similarity.

The determining of the result of the verification may includedetermining whether a total size of one or more matching regions, eachhaving a similarity meeting a predetermined threshold value, meets apredetermined threshold size using the finally updated matchingregion-based similarity, and determining whether the verification of theinput fingerprint image is successful based on a result of thedetermining of whether the total size meets the predetermined thresholdsize.

The determining of the result of the verification may include, inresponse to a similarity average value, of similarity valuesrespectively related to at least some of the plural matching regionsrepresented in the finally updated matching region-based similarity,meeting a predetermined threshold value, determining that theverification of the input fingerprint image is successful.

In one general aspect, a processor implemented fingerprint verificationmethod includes obtaining an input fingerprint image, incrementallyupdating a matching region-based similarity respectively based ondetermined similarities for respectively determined matching regionsbetween the input fingerprint image and each of plural registeredfingerprint images, determining respective scores with respect to eachof one or more of the incremental updatings of the matching region-basedsimilarity, or a final score based on a finally updated matchingregion-based similarity representing plural matching regions withrespect to at least a multiple of the plural registered fingerprintimages, determining a result of a verification of the input fingerprintimage based whether any of the respective scores or the final scoremeets a predetermined verification condition, and indicating thedetermined result of the verification.

The determining of the respective scores with respect to each of one ormore of the incremental updatings of the matching region-basedsimilarity may cease when a corresponding score, of the respectivescores, is determined in the determining of the result of theverification as meeting the predetermined verification condition.

In one general aspect, a fingerprint verification apparatus includes aprocessor configured to determine a matching region between an inputfingerprint image and a registered fingerprint image, determine asimilarity corresponding to the matching region, representing adetermined indication of similarities between the input fingerprintimage and the registered fingerprint image, relate the determinedsimilarity to the matching region as represented in a matchingregion-based similarity, determine a result of a verification of theinput fingerprint image based on the matching region-based similarity,and indicate the result of the verification.

The processor may be further configured to determine the matchingregion-based similarity based on the matching region between the inputfingerprint image and the registered fingerprint image and thesimilarity corresponding to the matching region between the inputfingerprint image and the registered fingerprint image.

The processor may be further configured to determine a score based onthe updated matching region-based similarity, and determine the resultof the verification based on whether the score satisfies a predeterminedfingerprint verification condition.

Other features and aspects will be apparent from the following detaileddescription, the drawings, and the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagram illustrating an example of a fingerprintverification method.

FIGS. 2A and 2B are diagrams illustrating examples of occurrence of afalse rejection and a false acceptance.

FIG. 3 is a diagram illustrating an example of a fingerprintverification method.

FIG. 4 is a flowchart illustrating an example of a fingerprintverification method.

FIG. 5 is a flowchart illustrating an example of a fingerprintverification method.

FIG. 6 is a diagram illustrating an example of a matching beingperformed between an input fingerprint image and a registeredfingerprint image.

FIGS. 7 through 9 are diagrams illustrating an example of a method ofdetermining a similarity between an input fingerprint image and aregistered fingerprint image.

FIG. 10 is a diagram illustrating an example of a method of updating amatching region-based similarity.

FIGS. 11A and 11B are diagrams illustrating an example of a method ofperforming a fingerprint verification based on a matching region-basedsimilarity.

FIG. 12 is a diagram illustrating an example of a fingerprintverification apparatus.

FIG. 13 is a diagram illustrating an example of a computing apparatus.

Throughout the drawings and the detailed description, unless otherwisedescribed or provided, the same drawing reference numerals will beunderstood to refer to the same or like elements, features, andstructures. The drawings may not be to scale, and the relative size,proportions, and depiction of elements in the drawings may beexaggerated for clarity, illustration, and convenience.

DETAILED DESCRIPTION

The following detailed description is provided to assist the reader ingaining a comprehensive understanding of the methods, apparatuses,and/or systems described herein. However, various changes,modifications, and equivalents of the methods, apparatuses, and/orsystems described herein will be apparent after an understanding of thedisclosure of this application. For example, the sequences of operationsdescribed herein are merely examples, and are not limited to those setforth herein, but may be changed as will be apparent after anunderstanding of the disclosure of this application, with the exceptionof operations necessarily occurring in a certain order. Also,descriptions of features that are known in the art may be omitted forincreased clarity and conciseness.

The features described herein may be embodied in different forms, andare not to be construed as being limited to the examples describedherein. Rather, the examples described herein have been provided merelyto illustrate some of the many possible ways of implementing themethods, apparatuses, and/or systems described herein that will beapparent after an understanding of the disclosure of this application.

Terms such as first, second, A, B, (a), (b), and the like may be usedherein to describe components. Each of these terminologies is not usedto define an essence, order, or sequence of a corresponding componentbut used merely to distinguish the corresponding component from othercomponent(s). For example, a first component may be referred to as asecond component, and similarly the second component may also bereferred to as the first component.

It should be noted that if it is described in the specification that onecomponent is “connected,” “coupled,” or “joined” to another component, athird component may be “connected,” “coupled,” and “joined” between thefirst and second components, although the first component may bedirectly connected, coupled or joined to the second component. Inaddition, it should be noted that if it is described in thespecification that one component is “directly connected” or “directlyjoined” to another component, a third component may not be presenttherebetween. Likewise, expressions, for example, “between” and“immediately between” and “adjacent to” and “immediately adjacent to”may also be construed as described in the foregoing.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting. As used herein, thesingular forms “a,” “an,” and “the,” are intended to include the pluralforms as well, unless the context clearly indicates otherwise. It willbe further understood that the terms “comprises,” “comprising,”“includes,” and/or “including,” when used herein, specify the presenceof stated features, integers, operations, elements, and/or components inan example embodiment, but do not preclude the presence or addition ofone or more other features, integers, operations, elements, components,and/or groups thereof in alternative embodiments, nor the lack of suchstated features, integers, operations, elements, components, and/orcombinations/groups thereof in further alternative embodiments unlessthe context and understanding of the present disclosure indicatesotherwise. The use of the term ‘may’ herein with respect to an exampleor embodiment, e.g., as to what an example or embodiment may include orimplement, means that at least one example or embodiment exists wheresuch a feature is included or implemented while all examples andembodiments are not limited thereto.

Unless otherwise defined, all terms, including technical and scientificterms, used herein have the same meaning as commonly understood by oneof ordinary skill in the art to which this disclosure pertains based onan understanding of the present disclosure. Terms, such as those definedin commonly used dictionaries, are to be interpreted as having a meaningthat is consistent with their meaning in the context of the relevant artand the present disclosure, and are not to be interpreted in anidealized or overly formal sense unless expressly so defined herein.

FIG. 1 is a diagram illustrating an example of a fingerprintverification method.

A fingerprint verification refers to a verification method used todetermine whether a user attempting at a verification using afingerprint is a valid user or not in user log-in, payment systems,and/or access control, as non-limiting examples. Referring to FIG. 1, afingerprint verification apparatus configured to perform such afingerprint verification is also represented by, or included in, acomputing apparatus 100. The computing apparatus 100 includes, forexample, a smartphone, a wearable device, a tablet computer, a netbook,a laptop computer, a desktop computer, a personal digital assistant(PDA), a set-top box, a home appliance, a biometrics-based door lock, asecurity device, and a vehicle start device. One or more processors ofthe computing apparatus 100 may be configured to perform the fingerprintverification. As another example, FIGS. 12 and 13 also demonstrate suchcomputing apparatus examples.

For example, the computing apparatus 100 may determine whether a userattempting to gain access or a greater access to the computing apparatus100 is a valid user by analyzing a fingerprint pattern of a fingerprintimage 120 sensed through a fingerprint sensor 110 of the computingapparatus 100. For example, in a case in which the user inputs afingerprint to the fingerprint sensor 110 to cancel a lock state of thecomputing apparatus 100, e.g., to ‘unlock’ the computing apparatus 100,the computing apparatus 100 compares the fingerprint image 120 obtainedthrough the fingerprint sensor 110 to at least one of registeredfingerprint images 142, 144, and 146 stored in a database (DB) 130, anddetermines whether to cancel the lock state of the computing apparatus100 based on a result of the comparing. The DB 130 may store registeredfingerprint images of at least one finger, and may be included in thecomputing apparatus 100 and/or may be included in a separate computingapparatus or remote cloud or server, for example.

In an example, a valid user may register, in advance, fingerprintinformation of the valid user in the computing apparatus 100, and thecomputing apparatus 100 may store the fingerprint information registeredby the valid user in the DB 130 or the example cloud or other serverstorage. The fingerprint information of the valid user may also beentered through another computing apparatus 100, and transferred to orrequested by the computing apparatus 100 of FIG. 1, or otherwiseacquired and stored in the DB 130. The registered fingerprintinformation may be stored in a form of a registered fingerprint image,for example, as color, gray scale, intensity, depth, or black and whiteimages. In another example, the registered fingerprint information ofthe registered fingerprint images 142, 144, or 146 may be stored asmagnitude images, such representative of image information after havingbeen frequency domain transformed or Fourier-Mellin transformed, asnon-limiting example, from such color, gray scale, intensity, depth, orblack and white images, while noting that the registered fingerprintinformation may still be stored and later utilized in still other forms.In a fingerprint registration process, a user may register variousfingerprint images, for example, the registered fingerprint images 142,144, and 146. In a fingerprint verification process, the computingapparatus 100 may compare the fingerprint image 120 obtained through thefingerprint sensor 110 to the registered fingerprint images 142, 144,and 146. Here, sizes of the fingerprint image 120 and the registeredfingerprint images 142, 144, and 146 may be determined by a recognitionregion of the fingerprint sensor 110, such as when the fingerprint image120 and the registered fingerprint images 142, 144, and 146 are acquiredby the same or like fingerprint sensor 110, noting that examples are notlimited thereto. In an example, due to a limited size of the recognitionregion of the fingerprint sensor 110, the fingerprint image 120 obtainedthrough the fingerprint sensor 110 and the registered fingerprint images142, 144, and 146 may include information associated with partialfingerprint regions, i.e., only a partial portion or partial region of afull fingerprint or full fingerprint region. Thus, the fingerprint image120 and the registered fingerprint images 142, 144, and 146 may each beobtained through the example fingerprint sensor 110 having such limitedrecognition area or region, and thus, may not include sufficientfeatures to be used to accurately verify the fingerprint image 120 basedon the partial fingerprint region represented by the fingerprint image120 and/or the partial fingerprint regions represented by the respectiveregistered fingerprint images 142, 144, and 146. For example, if anindependent fingerprint verification is performed based on a one-to-onecomparison of such a partial fingerprint image and a partial registeredfingerprint image, which both may have not sufficient differentiating oridentifying features, an undesirable result, such as, for example, afalse rejection or a false acceptance, may be obtained. An example ofsuch an undesirable result will be described hereinafter with referenceto FIGS. 2A and 2B.

FIG. 2A is a diagram illustrating an example of occurrence of a falserejection.

Referring to FIG. 2A, in a case in which a size of a matching region,i.e., the region where a match occurs, between a fingerprint image 210obtained through a fingerprint sensor and a registered fingerprint image220 is small or of limited area, also corresponding to there beinglimited differentiatable or identifiable features in either of thefingerprint image 210 and registered fingerprint image 220, it ispossible that the fingerprint image 210 may be rejected from being averified fingerprint due to the small size of the matching region evenif the respective fingerprint patterns in the matching region are thesame or substantially similar to each other. For example, to preventfalse acceptances that may occur when partial fingerprint regions, fromwhich a fingerprint may be less identifiable, are matched between acaptured fingerprint and a registered fingerprint, verification methodsmay require a size of the matching region to be greater than or equal toa preset size before the captured fingerprint can be considered tocorrespond to a fingerprint verification condition for a determinationthat the fingerprint verification is successful.

Thus, in the example of FIG. 2A, even though the fingerprint image 210is of a same finger as the registered fingerprint image, i.e., with thesame or substantial similarities in patterns, the fingerprint image 210may be rejected, and thus a false rejection.

FIG. 2B is a diagram illustrating an example of occurrence of a falseacceptance.

Referring to FIG. 2B, in a case in which a fingerprint pattern of afingerprint image 230 obtained through a fingerprint sensor and afingerprint pattern of a registered fingerprint image 240 of differentfingerprints are each less distinguishable, a matching region betweenthe fingerprint image 230 and the registered fingerprint image 240 maybe determined to be large due to respective simple fingerprint patternsof the fingerprint image 230 and the registered fingerprint image 240,and thus, the similarity between the fingerprint image 230 and theregistered fingerprint image 240 may be determined to be high and atypical verification method may verify the fingerprint image 230 as avalid fingerprint. However, because the fingerprint patters have suchrespective simple fingerprint patterns, even when the fingerprints areof different individuals the fingerprint image 230 may be validated dueto the large similarity and large matching region, and thus it is highlypossible that such false acceptances may occurs.

Such typical false rejections and false acceptances of FIGS. 2A and 2Bmay adversely affect an accuracy or a recognition rate in thetechnological implementations of fingerprint verification, and thusrepresent technological problems, found herein desiring of technologicalsolutions to prevent or more minimize such false rejections and falseacceptances from occurring. One or more examples to be describedhereinafter may, for example, present verification methods andimplementing apparatuses that may resolve such issues described in suchtypical technological approaches and provide technological approachesfor fingerprint verification with greater accurately and/or with greaterverification speed, as only examples.

FIG. 3 is a diagram illustrating an example of a fingerprintverification method.

Referring to FIG. 3, a fingerprint verification apparatus performs afingerprint verification based on determined similarities between afingerprint image 310 input for the fingerprint verification and each ofa plurality of registered fingerprint images 322, 324, 326, and 328. Thefingerprint verification apparatus performs the fingerprint verificationbased on determined respective matching regions between the inputfingerprint image 310 and each of the registered fingerprint images 322,324, 326, and 328, in addition to the determined similarities betweenthe input fingerprint image 310 and each of the registered fingerprintimages 322, 324, 326, and 328. For example, a determined matching regionmay correspond to a determined area or relative size of a matchingportion or area between the input fingerprint image and a registeredfingerprint image. The fingerprint verification apparatus determines amatching region-based similarity with respect to the input fingerprintimage 310. For example, the matching region-based similarity includessimilarity information associated with a similarity between the inputfingerprint image 310 and one or more registered fingerprint images, andmay be related to a region corresponding to the input fingerprint image310 represented in the matching region-based similarity, e.g., thesimilarity information may be allocated to a matching region includedthe matching region-based similarity, such as when the matchingregion-based similarity is represented as an image. The fingerprintverification apparatus respectively determines similarities and matchingregions, or respective overlapping regions, between fingerprintpatterns, for each comparing of the input fingerprint image 310 to eachof the registered fingerprint images 322, 324, 326, and 328, and witheach comparison the fingerprint verification apparatus updates theexample matching region-based similarity based on each determinedmatching region and determined similarities corresponding to thedetermined matching regions.

For example, in FIG. 3, the reference numeral 330 indicates a visualrepresentation of such a matching region-based similarity. The matchingregion-based similarity is represented as an integration of respectivesimilarities or respective similarity information between the inputfingerprint image 310 and each of registered fingerprint images 322,324, 326, and 328. The matching region-based similarity includesinformation associated with the respective matching or overlappingregions and determined respective similarities or similarity informationbetween the input fingerprint image 310 and each of the registeredfingerprint images 322, 324, 326, and 328 for the matching regions.

For example, to determine such a matching region-based similarity, thefingerprint verification apparatus determines an example matching region332 and a corresponding similarity S₁ between the input fingerprintimage 310 and the registered fingerprint image 322. The fingerprintverification apparatus then updates a matching region-based similarityby allocating the similarity S₁ to the matching region 332, of an entireregion corresponding to the input fingerprint image 310 in the matchingregion-based similarity. The matching region-based similarity may begenerated or set, e.g., based on an entire region corresponding to theinput fingerprint image 310, before, during, or after the determining ofthe matching region 332 and similarity S₁, e.g., with the fingerprintverification apparatus updating the generated or set matchingregion-based similarity based on the determined matching region 332 andcorrespondingly determined similarity S₁. Here, as an example of thematching region-based similarity being generated or set based on anentire region corresponding to the input fingerprint image 310 (or anyof the registered fingerprint images), reference 330 in FIG. 3illustrates that the matching region-based similarity may have a size orarea the same as, or related or relative to, the input fingerprint image310, with the example matching region 332 being illustrated as occupyingor covering the illustrated portion of the whole of the matchingregion-based similarity, e.g., occupying or covering an illustratedportion of an area corresponding to a whole area of the inputfingerprint image 310. In operation 340, the fingerprint verificationapparatus may then determine a score for the matching region-basedsimilarity and determine whether that score satisfies a fingerprintverification condition. In response to the score not satisfying thefingerprint verification condition, the fingerprint verificationapparatus may proceed to compare the input fingerprint image 310 and theregistered fingerprint image 324, i.e., subsequent to the previouscomparison with respect to the registered fingerprint image 322. Thedetermined score in operation 340 refers to value, as only an example,that may be used to determine whether the fingerprint verification issuccessful or not, e.g., based on whether the example value meets apredetermined reference value. With the comparing of the inputfingerprint image 310 and the registered fingerprint image 324, thefingerprint verification apparatus determines a matching region 334 anda similarity S₂ between the input fingerprint image 310 and theregistered fingerprint image 324, and updates the previouslydetermined/updated matching region-based similarity based on thematching region 334 and the similarity S₂. For example, the illustratedmatching region-based similarity illustrates a bound region (full anddashed lines) that is illustrated as including the similarity S₂. Aswill be discussed in greater detail further below, though there may beadditional matching portions between the input fingerprint image 310 andthe registered fingerprint image 324 outside the example bound region ofmatching region 334, e.g., which could overlap with the illustratedbound region of matching region 332 illustrated as including thesimilarity S₂ and/or bound region of matching region 336 illustrated asincluding the similarity S₃, these additional matching portions may notbe updated or reflected in the matching region-based similarity withrespect to the comparison of the input fingerprint image 310 and theregistered fingerprint image 324 if either of the similarity S₁ and/orsimilarity S₃ indicate greater similarities than similarity S₂. Thus,operation 340 may be repeated again with respect to the matchingregion-based similarity that has been updated with respect to thematching region 334 and a similarity S₂, with the fingerprintverification apparatus determining whether a score determined based onthe latest updated matching region-based similarity satisfies thefingerprint verification condition. In response to the score notsatisfying the fingerprint verification condition, the fingerprintverification apparatus then performs similarly the forgoing on the nextregistered fingerprint image 326. In such a case, the matchingregion-based similarity is again updated again based on a matchingregion 336 and a similarity S₃ between the input fingerprint image 310and the registered fingerprint image 326. Thus, the fingerprintverification apparatus repeatedly updates the matching region-basedsimilarity by comparing the input fingerprint image 310 and each of theregistered fingerprint images 322, 324, 326, through the n-th registeredfingerprint image 328 in sequential order until the fingerprintverification condition is satisfied or all registered fingerprint imageshave been considered. In the above example, due to the sequentialdetermination of whether the fingerprint verification condition issatisfied based on each sequentially determined score corresponding toeach updating of the matching region-based similarity, only some of theregistered fingerprint images 322, 324, 326, through 328 may ultimatelyneed to be compared to the input fingerprint image 310 before theverification condition is met, e.g., instead of having compare all theregistered fingerprint images 322, 324, 326, through 328 to the inputfingerprint image 310 before ultimately determining whether theverification condition is met, and thus the fingerprint verification maybe terminated more rapidly and faster processing may be enabled if theverification condition is met earlier in the example sequentialperformances of operation 340.

As noted, in the example of FIG. 3, a determination of whether afingerprint verification condition is satisfied may be made each timethe matching region-based similarity is updated. However, in an example,the initial determination of whether fingerprint verification conditionis satisfied may alternatively be determined after a number of updateshave been performed or lastly after a final updating of the matchingregion-based similarity based on the n-th registered fingerprint image328. For example, all the matching regions and similarities between theinput fingerprint image 310 and the registered fingerprint images 322,324, 326, through 328 may be determined, and the determination ofwhether the fingerprint verification condition is satisfied may then bemade after the matching region-based similarity is finally updated. Inanother example, all the matching regions and similarities between theinput fingerprint image 310 and the registered fingerprint images 322,324, 326, through 328 may be determined, then the matching region-basedsimilarity may be generated or set based on analyses of all of thedetermined matching regions and similarities, and then the exampleoperation 340 of FIG. 3 may be performed to determine whether thefingerprint verification condition is satisfied. In another example, aninitial fast determination may be made to discern which registeredfingerprint images to consider, and in which order, such as based onresults of an initial fast, e.g., phase-only correlation (PoC),similarity determination operation with respect to the input fingerprintimage 310 and each of the registered fingerprint images, prior to moredetailed similarity comparisons being performed, such as the exampleFourier-Mellin method described in greater detail with reference toFIGS. 7 through 9. In addition, in the above, examples are discussedwhere determination of whether a fingerprint verification condition issatisfied, based on a correspondingly determined score, is made eachtime the matching region-based similarity is updated, sequentiallyperformed after each of a predetermined or set number or all of thematching region-based similarity updates are performed, examples alsoexist where respective determinations of whether a fingerprintverification condition is satisfied, based on a correspondinglydetermined score, may be made each time the matching region-basedsimilarity is updated for each of a predetermined or set number ofregistered fingerprint images, and thereafter the next determining ofwhether the fingerprint verification condition is satisfied, based on acorrespondingly determined score, delayed until a further predeterminedor set number, or all, of remaining registered fingerprint images havebeen considered in respective the matching region-based similarityupdates.

Thus, in one or more examples, a result of the fingerprint verificationmay not be determined based solely on an independently determinedsimilarity between an input fingerprint image and a single registeredfingerprint image, but may be determined based on a matchingregion-based similarity, which may be representative of incrementallycombined results of respective comparisons of the input fingerprintimage and plural registered fingerprint images, e.g., representative ofincrementally combined results of respective comparisons of the inputfingerprint image and plural registered fingerprint images in sequentialorder. Thus, in an example, a probability of occurrence of a falserejection or a false acceptance may be reduced compared to independentverification operations between an input fingerprint and each of two ormore registered fingerprints, and thus an accuracy in the fingerprintverification and a recognition rate may be improved in an example.

FIGS. 4 and 5 are flowcharts illustrating an example of a fingerprintverification method. It should be noted that in alternativeimplementations, the functions/acts noted may occur in other orders,e.g., including operations being performed in a reverse order, thannoted in the flowcharts. In addition, for example, two steps oroperations illustrated in succession in the examples of FIGS. 4 and 5may alternatively be executed substantially concurrently, depending uponthe functionality/acts involved in such various alternative examples.

Referring to FIG. 4, in operation 410, a fingerprint verificationapparatus obtains, e.g., by capturing, reading from a memory, and/orreceiving, an input fingerprint image. The input fingerprint imagerefers to a fingerprint image, e.g., a target on which a fingerprintverification is to be performed, and may be obtained through afingerprint sensor of the fingerprint verification apparatus, forexample, or by a separate or even remote fingerprint sensor. In anexample, the fingerprint sensor is configured to sense or capture onlyan image or features of only a portion of the whole of a finger thatpositioned relative to or applied to the fingerprint sensor. Inaddition, in an example, the fingerprint verification apparatus performsa preprocessing operation on the obtained input fingerprint image. Thepreprocessing operation may be performed to process the inputfingerprint image to be in a form, shape, or orientation more suitablefor the fingerprint verification by, for example, improving a quality ofthe input fingerprint image and adjusting a size of the inputfingerprint image. The preprocessing operation may include removingnoise from the input fingerprint image, increasing a contrast of theinput fingerprint image, deblurring the input fingerprint image,performing warping to correct a distortion in the input fingerprintimage, binarizing the input fingerprint image, normalizing the size ofthe input fingerprint image, and/or cropping the input fingerprintimage, as only non-limiting examples.

In operation 420, the fingerprint verification apparatus determines amatching region-based similarity based on a determined matching regionbetween the input fingerprint image and at least one registeredfingerprint image. The fingerprint verification apparatus selects aregistered fingerprint image to be compared to the input fingerprintimage from a plurality of registered fingerprint images stored in a DB,and calculates a similarity that indicates how similar the fingerprintpattern of the selected registered fingerprint image is to thefingerprint pattern of the input fingerprint image. Here, a determinedhigh similarity indicates that the fingerprint pattern of the inputfingerprint image is relatively considerably similar to the fingerprintpattern of the registered fingerprint image. Likewise, a determined lowsimilarity indicates that the fingerprint pattern of the inputfingerprint image is relatively dis-similar to the fingerprint patternof the registered fingerprint image.

In one example, the fingerprint verification apparatus determines thematching region between the input fingerprint image and the registeredfingerprint image using rotation information and translation informationdetermined between the input fingerprint image and the registeredfingerprint image, and calculates the similarity between the fingerprintpatterns in/for the matching region. The rotation and translationinformation may correspond to the rotation and translation of either orboth of the input fingerprint image and the registered fingerprint imagethat thereby aligns individual patterns, for example, of the respectivefingerprint patterns, such as discussed in greater detail further belowwith respect to FIG. 6. Thus, the matching region refers to afingerprint region, corresponding to both the input fingerprint imageand the registered fingerprint image, where it is estimated that theinput fingerprint image and the registered fingerprint image have a mostsame or similar fingerprint patterns. A method of determining thematching region-based similarity may include calculating the similaritybetween the input fingerprint image and the registered fingerprintimage, which may be represented numerically, and allocating thecalculated similarity to the determined matching region between theinput fingerprint image and the registered fingerprint image. Forexample, in the above example of FIG. 3, the matching region 332 may bedetermined and the calculated similarity S₁ allocated to that matchingregion 332 in/of the accordingly generated or set matching region-basedsimilarity for the current verification operation with respect to theinput fingerprint image and the one or more registered fingerprintimages.

In one example, the fingerprint verification apparatus uses, as thesimilarity between the input fingerprint image and the registeredfingerprint image, a feature value obtained by the fingerprintverification apparatus performing a fast Fourier transform (FFT) on theinput fingerprint image and the registered fingerprint image. Forexample, the fingerprint verification apparatus calculates thesimilarity using an image frequency information-based matching method,such as, for example, a Fourier-Mellin method performed by thefingerprint verification apparatus. The similarity may be determinedbased on phase correlation information obtained by the fingerprintverification apparatus using the Fourier-Mellin method, or determined bythe fingerprint verification apparatus based on the rotation informationand the translation information between the input fingerprint image andthe registered fingerprint image, in addition to the phase correlationinformation, as determined by the fingerprint verification apparatus. Anexample of a method of determining the similarity based on theFourier-Mellin method will be described in greater detail with referenceto FIGS. 7 through 9, noting that the method of determining thesimilarity between the input fingerprint image and the registeredfingerprint image is not limited to the example Fourier-Mellin method,and in various examples various other methods may be used to determine asimilarity between the fingerprint patterns of the input fingerprintimage and the registered fingerprint image. For example, the similaritymay be determined by the fingerprint verification apparatus based on adistribution or a form of feature points extracted by the fingerprintverification apparatus from the fingerprint patterns of the inputfingerprint image and the registered fingerprint image. Another method,other than the example, Fourier-Mellin method, may include a method ofdiscovering minutiae, as major feature(s) of a fingerprint, andperforming aligning, matching, and similarity determinations based on adetermined relationship between the minutiae.

The fingerprint verification apparatus updates the matching region-basedsimilarity based on the calculated similarity. The matching region-basedsimilarity may be initially set to have default values, for example, 0for an allocated similarity of an entirety of the matching region-basedsimilarity. Thus, the fingerprint verification apparatus may record orupdate the calculated similarity in a corresponding indicated region ofthe matching region-based similarity corresponding to the matchingregion between the input fingerprint image and the registeredfingerprint image. A score may be determined for the matchingregion-based similarity, and in response to the score not satisfying apreset fingerprint verification condition, the fingerprint verificationapparatus may proceed to calculate a similarity between the inputfingerprint image and another registered fingerprint image, may thenupdate the matching region-based similarity based on the result of thatcalculated similarity, and may again determine whether a score of thematching region-based similarity satisfies the preset fingerprintcondition.

In one example, the fingerprint verification apparatus determines afirst similarity corresponding to a first matching region between theinput fingerprint image and a first registered fingerprint image. Thefingerprint verification apparatus may thus update the matchingregion-based similarity based on the first similarity and the firstmatching region. In response to a score determined based on the updatedmatching region-based similarity not satisfying the fingerprintverification condition, the fingerprint verification apparatusdetermines a second similarity corresponding to a second matching regionbetween the input fingerprint image and a second registered fingerprintimage. Here, the previous updating of the matching region-basedsimilarity based on the first similarity and the first matching regionmay include allocating the first similarity to a region of the matchingregion-based similarity representing the first matching region. Forexample, when the matching region-based similarity has a same area,form, or size as the input fingerprint image, the region of the matchingregion-based similarity representing the first matching region maymerely be an indication of the first matching region in or with respectto the matching region-based similarity, such as demonstrated above withrespect to FIG. 3 and the matching region 332 being in/of theaccordingly generated or set matching region-based similarity indicatedby the reference numeral 330. Thus, with the fingerprint verificationapparatus having determined the second similarity corresponding to thesecond matching region, the fingerprint verification apparatus mayupdate the matching region-based similarity based on the secondsimilarity and the second matching region. The fingerprint verificationapparatus updates the matching region-based similarity by allocating thesecond similarity to a region of the matching region-based similarityrepresenting the second matching region. Here, when an overlap occursbetween the first matching region and the second matching region, e.g.,they overlap each other with respect to the input fingerprint image,when the second similarity and second matching region are allocated tothe matching region-based similarity the fingerprint verificationapparatus selectively allocates the greater of the first similarity andthe second similarity to the region of the matching region-basedsimilarity corresponding to the overlapping region. The fingerprintverification apparatus further allocates the second similarity to aremaining region of the matching region-based similarity representingthe remaining portion of the second matching region in which theoverlapping region is not included. According to such an example, foreach remaining registered fingerprint that has not been yet beencompared to the input fingerprint image, respective comparisons betweenthe input fingerprint image and each of the remaining registeredfingerprint images may be performed in sequential order, with thematching region-based similarity being incrementally or continuouslyupdated based on the result of each respective comparison, until thefingerprint verification condition is satisfied or all registeredfingerprints have been considered and the fingerprint verificationcondition is still not met. For example, when the fingerprintverification condition is satisfied after only half of the registeredfingerprints have been considered, the fingerprint verificationapparatus may cease operations and indicate the verification success inoperation 430 without having to perform all such comparisons with allregistered fingerprint images in the fingerprint verification process.

In another example, the fingerprint verification apparatus may firstdetermine the respective similarities between the input fingerprintimage and each of all of the registered fingerprint images, and maydetermine a matching region-based similarity based on the determinedrespective similarities. In this example, the fingerprint verificationapparatus determines the respective matching regions and thesimilarities between the input fingerprint image and each of theregistered fingerprint images, and then updates the matchingregion-based similarity based on the determined matching regions and thedetermined similarities. Here, in response to any overlapping regionsbeing present between any of the matching regions, the fingerprintverification apparatus selectively allocates, to an example overlappingregion, a greatest similarity among similarities corresponding to thecorresponding matching regions that overlap each other. Similarities foreach of such overlapping regions may similarly be selectively allocated.According to such an example, the respective similarities between theinput fingerprint image and each of all of the registered fingerprintimages are calculated, and whether the fingerprint verificationcondition is satisfied is then determined after the matchingregion-based similarity is finally determined based on the calculatedsimilarities, determined matching regions, and any determinedoverlapping regions.

In operation 430, the fingerprint verification apparatus determines aresult of the fingerprint verification of the input fingerprint imagebased on the matching region-based similarity. For example, operation430 may correspond to operation 340 of FIG. 3, and thus discussionsabove with respect to operation 430 are not repeated here merely forbrevity purposes. As noted, in response to the score determined based onthe matching region-based similarity satisfying the fingerprintverification condition, the fingerprint verification apparatusdetermines that the fingerprint verification of the input fingerprintimage is successful.

In one example, the fingerprint verification apparatus determineswhether the fingerprint verification is successful based on whether ascore determined based on the most recent updated matching region-basedsimilarity, e.g., each time the matching region-based similarity isupdated, satisfies the fingerprint verification condition. For example,the fingerprint verification apparatus may determine and indicatewhether the fingerprint verification is successful or may determine andindicate whether the verification is unsuccessful.

In one example, the fingerprint verification apparatus determineswhether a total size of matching regions, represented in the matchingregion-based similarity, having similarities greater than a thresholdvalue is greater than a threshold size based on the matchingregion-based similarity, and determines whether the fingerprintverification of the input fingerprint image is successful based on aresult of the determining. In response to the total size of the matchingregions having similarities greater than the threshold value beinggreater than the threshold size, the fingerprint verification apparatusdetermines that the fingerprint verification of the input fingerprintimage is successful. In another example, in response to an average valueof the allocated similarities of the matching region-based similaritybeing greater than a threshold value, the fingerprint verificationapparatus determines that the fingerprint verification of the inputfingerprint image is successful. The fingerprint verification apparatusmay indicate the result of the fingerprint verification process eitherexplicitly or implicitly. For example, an explicit indication mayinclude a display or audible announcement of the success of thefingerprint verification process and an implicit indication may includethe fingerprint verification apparatus selectively performing or ceasingto perform additional operations of the fingerprint verificationapparatus. For example, in response to the fingerprint verificationbeing determined to be successful, the fingerprint verificationapparatus may perform the implicit indication by cancelling a lock stateof a computing apparatus represented by, connected to, or including thefingerprint verification apparatus, or by assigning, to a user, a rightor authority to access one or more functions or features of the examplecomputing apparatus or fingerprint verification apparatus. In a case inwhich a score, determined based on a matching region-based similaritydetermined with respect to all registered fingerprint images, does notsatisfy the fingerprint verification condition, the fingerprintverification apparatus may determine that the fingerprint verificationof the input fingerprint image is unsuccessful. In response to thefingerprint verification being determined to be unsuccessful, thefingerprint verification apparatus may similarly indicate theunsuccessful either explicitly or implicitly, e.g., with an implicitindication being the computing apparatus or verification apparatusmaintaining the example lock state or restricting the right or authorityof the user for the access to the one or more functions or features ofthe computing apparatus or fingerprint verification apparatus. Suchand/or further examples of methods of determining whether thefingerprint verification is successful and/or unsuccessful will bedescribed in greater detail below with reference to FIG. 11A.

FIG. 5 is a flowchart illustrating an example of a fingerprintverification method. As only an example, FIG. 5 may be a more detailedexample of the method described with reference to FIG. 4. Thus, as anexample, the above descriptions provided with reference to FIG. 4 arealso applicable to corresponding operations of the description providedhereinafter with reference to FIG. 5, and thus repeated descriptionsthereof will be omitted here merely for brevity purposes.

Referring to FIG. 5, in operation 510, a fingerprint verificationapparatus obtains, e.g., captures, reading, and/or receives, an inputfingerprint image. In operation 520, the fingerprint verificationapparatus performs a matching operation of the input fingerprint imageto a registered fingerprint image. The matching may include rotatingand/or translating at least one of the input fingerprint image and theregistered fingerprint image, and determining a matching region betweenthe input fingerprint image and the registered fingerprint image.

In operation 530, the fingerprint verification apparatus determines asimilarity, based on the matching region determined in operation 520,between the input fingerprint image and the registered fingerprintimage. For example, the fingerprint verification apparatus determines afirst similarity corresponding to a first matching region between theinput fingerprint image and a first registered fingerprint image.

In operation 540, the fingerprint verification apparatus generates,sets, or updates a matching region-based similarity based on thesimilarity determined in operation 530. For example, the fingerprintverification apparatus may update the generated or set matchingregion-based similarity based on the matching region between the inputfingerprint image and the registered fingerprint image, and based on thedetermined similarity corresponding to the matching region between theinput fingerprint image and the registered fingerprint image. Forexample, the fingerprint verification apparatus may apply the similaritydetermined in operation 530 to a previously determined matchingregion-based similarity with respect to a region of the previouslydetermined matching region-based similarity corresponding to thematching region. Here, in an example where the matching region-basedsimilarity has previously had a previously determined similarly appliedto a region of the matching region-based similarity that overlaps withthe matching region determined in operation 520, i.e., a correspondingoverlapping region, the greater similarity between the previouslyallocated similarity and the newly determined similarity may beallocated to the corresponding overlapping region.

In operation 550, the fingerprint verification apparatus determineswhether a score determined based on the matching region-based similaritysatisfies a fingerprint verification condition. For example, thefingerprint verification apparatus calculates a score to determinewhether a fingerprint verification is successful based on the matchingregion-based similarity determined based on the first similarity, anddetermines whether the calculated score satisfies the fingerprintverification condition. In operation 560, in response to the fingerprintverification condition being satisfied, the fingerprint verificationapparatus determines that the fingerprint verification is successful andterminates a fingerprint verification process. Conversely, in operation570, in response to the fingerprint verification condition not beingsatisfied, the fingerprint verification apparatus may determine whethersimilarities of all registered fingerprint images have been determined.

In operation 580, in response to the similarities of all the registeredfingerprint images having been determined, the fingerprint verificationapparatus determines that the fingerprint verification is unsuccessfuland terminates the fingerprint verification process. In operation 590,in response to the determination that the similarities of all theregistered fingerprint images have not been determined, the fingerprintverification apparatus selects another or subsequent registeredfingerprint image from the registered fingerprint images and thenrepeats operations 520, 530, 540, 550, and 570 on the selectedregistered fingerprint image.

For example, the fingerprint verification apparatus calculates a scoreusing the matching region-based similarity determined based on the firstsimilarity. In response to the calculated score not satisfying thefingerprint verification condition, the fingerprint verificationapparatus selects a second registered fingerprint image subsequent tothe first registered fingerprint image in operation 590. The fingerprintverification apparatus then matches the input fingerprint image to thesecond registered fingerprint image in operation 520, and determines asecond similarity corresponding to a second matching region between theinput fingerprint image and the second registered fingerprint image inoperation 530. The fingerprint verification apparatus then updates thematching region-based similarity based on the second similarity inoperation 540. Here, in response to an overlapping region beingdetermined to be present between the first matching region and thesecond matching region, the fingerprint verification apparatus allocatesthe greater similarity between the first similarity and the secondsimilarity to the overlapping region. The fingerprint verificationapparatus also allocates the second similarity to the remaining regionof the second matching region in which the overlapping region is notincluded, to complete the updating of the matching region-basedsimilarity. The fingerprint verification apparatus determines whether ascore determined by the matching region-based similarity updated basedon the second similarity satisfies the fingerprint verificationcondition in operation 550. In response to the fingerprint verificationcondition not being satisfied and there still being available registeredfingerprint image(s) remaining, the fingerprint verification apparatusselects another or next registered fingerprint image in operation 590,and again performs the operations described above on the selectedregistered fingerprint image.

FIG. 6 is a diagram illustrating an example of matching between an inputfingerprint image and a registered fingerprint image.

Referring to FIG. 6, a fingerprint verification apparatus estimatesrotation information and translation information of an input fingerprintimage 610 and a registered fingerprint image 620, and determines amatching region 630 between the input fingerprint image 610 and theregistered fingerprint image 620 using the estimated rotationinformation and the estimated translation information. In one example,for the matching between the input fingerprint image 610 and theregistered fingerprint image 620, a method of matching patterns orfeatures of a pixel intensity of an image in a space, or a method ofdetermining a parameter needed for matching between two images in afrequency domain of the images may be used.

FIG. 7 is a flowchart illustrating an example of a method of determininga similarity between an input fingerprint image and a registeredfingerprint image based on a Fourier-Mellin method.

Referring to FIG. 7, in operation 710, a fingerprint verificationapparatus transforms information of a spatial domain included in aninput fingerprint image to information of a frequency domain using anFFT. In operation 730, the fingerprint verification apparatus transformsinformation of a spatial domain included in a registered fingerprintimage to information of a frequency domain using an FFT. As only anexample, the information of the frequency domain may be based on anorthogonal coordinates system that represents information using, forexample, two-dimensional (2D) (x, y) coordinates.

In operation 715, the fingerprint verification apparatus transforms acoordinates system of the information of the frequency domain includedin the input fingerprint image to a polar coordinates system, forexample, such as by using a log-polar transform (LPT). For example, theLPT may be performed on a magnitude value of a pixel in an FFT imageobtained through the FFT. In the polar coordinates system, informationmay be represented by a radius, an angle, or a combination thereof. Inoperation 735, the fingerprint verification apparatus applies an LPT tothe information of the frequency domain included in the registeredfingerprint image. The LPT will be described in greater detail withreference to FIG. 8.

FIG. 8 is a diagram illustrating an example of an LPT. Referring to FIG.8, in an orthogonal coordinates system, concentric circles are set basedon a central point 810. The concentric circles are divided into aplurality of regions based on a radius, an angle, or a combinationthereof. For example, an LPT maps the plurality of regions in theorthogonal coordinates system to a plurality of regions in a polarcoordinates system represented by a radius and an angle. In such anexample, the central point 810 in the orthogonal coordinates system maybe mapped by the verification apparatus to a region 815 corresponding to(0, 0°) in the polar coordinates system. Similarly, a first region 820,a second region 830, a third region 840, and a fourth region 850 in theorthogonal coordinates system may be mapped by the verificationapparatus to a first region 825, a second region 835, a third region845, and a fourth region 855, respectively, in the polar coordinatessystem.

The LPT may map a plurality of regions in the orthogonal coordinatessystem to a plurality of regions in the polar coordinates systemrepresented based on an angle. In such a case, the first region 820 inthe orthogonal coordinates system may be mapped by the verificationapparatus to a (0°) region in the polar coordinates system. The secondregion 830 and the third region 840 in the orthogonal coordinates systemmay be mapped by the verification apparatus to a (36°) region in thepolar coordinates system, and the fourth region 840 in the orthogonalcoordinates system may be mapped by the verification apparatus to a(324°) region in the polar coordinates system, as only examples.

Referring back to FIG. 7, in operation 720, the fingerprint verificationapparatus applies an FFT to the input fingerprint image to which the LPTis applied. In operation 740, the fingerprint verification apparatusapplies an FFT to the registered fingerprint image to which the LPT isapplied. In operation 750, the fingerprint verification apparatusperforms a phase correlation based on a result obtained through the FFT,and detects a peak as a result of performing the phase correlation. Alocation of the detected peak indicates rotation information between theinput fingerprint image and the registered fingerprint image.

In another example, the location of the detected peak may indicate scaleinformation between the input fingerprint image and the registeredfingerprint image. For example, one axis of an image obtained throughthe LPT may correspond to an angle, and the other axis of the image maycorrespond to a radius, and thus the location of the peak detectedthrough the phase correlation may be indicated by a (a coordinate of theaxis corresponding to an angle, a coordinate of the axis correspondingto a radius). The coordinate of the axis corresponding to an angle mayindicate the rotation information, and the coordinate of the axiscorresponding to a radius may indicate the scale information.

In an example, the fingerprint verification apparatus may not adjust orchange a scale of the fingerprint image, or otherwise the fingerprintimage may not have a change in scale, and thus a radius may be fixed toa preset value, for example, 1. In such an example, the location of thepeak detected through the phase correlation may be represented by thecoordinate of the axis corresponding to an angle, and the coordinate ofthe axis corresponding to an angle may indicate the rotationinformation.

In one example, the fingerprint verification apparatus detects a peakvalue by performing the phase correlation, and determines a similaritybetween the input fingerprint image and the registered fingerprint imagebased on the peak value. As a size of a region, for example, anoverlapping region, in which a fingerprint pattern of the inputfingerprint image and a fingerprint pattern of the registeredfingerprint image are the same or similar to each other increases, or assimilarity between the fingerprint pattern of the input fingerprintimage and the fingerprint pattern of the registered fingerprint imageincreases, the peak value may tend to increase. Based on such atendency, the fingerprint verification apparatus may determine thesimilarity between the input fingerprint image and the registeredfingerprint image based on the peak value detected through the phasecorrelation.

The fingerprint verification apparatus rotates the input fingerprintimage based on the rotation information θ in operation 760, and appliesan FFT on the rotated input fingerprint image in operation 770. Inoperation 780, the fingerprint verification apparatus performs a phasecorrelation based on the input fingerprint image to which the FFT isapplied in operation 770 and the registered fingerprint image to whichthe FFT is applied in operation 730. As a result of performing the phasecorrelation, a peak is detected, and a location of the detected peakindicates translation information (Tx, Ty) between the input fingerprintimage and the registered fingerprint image. In operation 790, thefingerprint verification apparatus translates the input fingerprintimage rotated in operation 760 based on the translation information (Tx,Ty).

The fingerprint verification apparatus then matches the inputfingerprint image and the registered fingerprint image by rotating andtranslating the input fingerprint image based on the rotationinformation and the translation information obtained through the exampleFourier-Mellin method. In one example, the fingerprint verificationapparatus determines a similarity based on a matching region determinedby the matching between the rotated and translated input fingerprintimage and the registered fingerprint image. The fingerprint verificationapparatus may determine the similarity using various methods. Forexample, in one example, the fingerprint verification apparatusdetermines the similarity based on a brightness value-based normalizedcross correlation method. For example, the fingerprint verificationapparatus may determine the similarity based on a correlation obtainedthrough the below Equation 1, for example.

$\begin{matrix}{{{ncc}\left( {I_{1},I_{2}} \right)} = \frac{\Sigma_{{({i,j})} \in W}{{I_{1}\left( {i,j} \right)} \cdot {I_{2}\left( {{x + i},{y + j}} \right)}}}{\sqrt[2]{\Sigma_{{({i,j})} \in W}{{I_{1}^{2}\left( {i,j} \right)} \cdot \Sigma_{{({i,j})} \in W}}{I_{2}^{2}\left( {{x + i},{y + j}} \right)}}}} & {{Equation}\mspace{14mu} 1}\end{matrix}$

In Equation 1, W denotes a matching region between an image I₁ and animage I₂, and ncc(I₁, I₂) denotes a normalized cross correlation in thematching region W between the image I₁ and the image I₂. For example,the image I₁ may be a rotated and translated input fingerprint image,and the image I₂ may be a registered fingerprint image. i denotes anx-axis coordinate of a pixel in the matching region W, and j denotes ay-axis coordinate of the pixel in the matching region W. x denotestranslation information Tx in an x-axis direction, and y denotestranslation information Ty in a y-axis direction. I₁(i, j) denotes apixel value on (i, j) coordinates of the image I₁, and I₂(x+i, y+j)denotes a pixel value on (x+i, y+j) coordinates of the image I₂. Thus,the correlation ncc(I₁, I₂) in the matching region W that is calculatedthrough Equation 1 above may be used as a similarity between the inputfingerprint image and the registered fingerprint image. In such anexample, extents of the matching region W may also be determined basedon the number of pixels for which a resulting ncc value is greater thana threshold value.

Although rotating and translating an input fingerprint image isdescribed with reference to FIG. 7, the rotating and translating may beperformed on a registered fingerprint image based on a result of a phasecorrelation without the rotating and translating of the inputfingerprint image. Alternatively, rotating and translating may beperformed on both the input fingerprint image and the registeredfingerprint image.

FIG. 9 is a diagram illustrating an example of a method of determining asimilarity between an input fingerprint image and a registeredfingerprint image based on a Fourier-Mellin method performed by averification apparatus.

Referring to FIG. 9, a registered fingerprint image 910 is transformedby the verification apparatus to a first LPT image 915 through an FFTand an LPT. An input fingerprint image 920 is transformed by theverification apparatus to a second LPT image 925 through an FFT and anLPT.

Through a phase correlation 930 between the first LPT image 915 and thesecond LPT image 925 by the verification apparatus, rotation informationθ between the registered fingerprint image 910 and the input fingerprintimage 920 is determined by the verification apparatus. In one example, asimilarity between the registered fingerprint image 910 and the inputfingerprint image 920 is determined by the verification apparatus basedon a peak value detected by the verification apparatus through the phasecorrelation 930.

The input fingerprint image 920 is rotated by the verification apparatusbased on the rotation information θ determined through the phasecorrelation 930. In addition, translation information (Tx, Ty) betweenthe registered fingerprint image 910 and the input fingerprint image 920is determined by the verification apparatus through a phase correlation950 between an FFT image, which is an image obtained as a result ofperforming an FFT on the registered fingerprint image 910 by theverification apparatus, and an FFT image, which is an image obtained asa result of performing an FFT on a rotated input fingerprint image 940by the verification apparatus.

Matching between the registered fingerprint image 910 and the inputfingerprint image 920 is performed by the verification apparatus basedon the rotation information θ and the translation information (Tx, Ty),and a matching region 970 between the registered fingerprint image 910and the input fingerprint image 920 is thereby determined by theverification apparatus. In one example, a correlation corresponding tothe matching region 970 in a matching image 960 between the registeredfingerprint image 910 and the input fingerprint image 920 is calculatedby the verification apparatus based on Equation 1 above, and thecalculated correlation is determined to be the similarity between theregistered fingerprint image 910 and the input fingerprint image 920 bythe verification apparatus.

In a matching region-based similarity, the similarity determined basedon the peak value detected through the phase correlation 930 or on thecorrelation calculated through Equation 1 is allocated by theverification apparatus to the matching region 970.

FIG. 10 is a diagram illustrating an example of a method of updating amatching region-based similarity.

Referring to FIG. 10, in operation 1010, a fingerprint verificationapparatus compares an input fingerprint image 1000 and a firstregistered fingerprint image 1022, among a plurality of registeredfingerprint images, determines a first matching region 1032 and a firstsimilarity between the input fingerprint image 1000 and the firstregistered fingerprint image 1022, and updates a matching region-basedsimilarity based on the first matching region 1032 and the firstsimilarity. The reference numeral 1015 in FIG. 10 indicates avisualization of the matching region-based similarity determined inoperation 1010. Here, in an example where the first similarity isdetermined to be 0.97, the fingerprint verification apparatus allocatesthe first similarity 0.97 to the illustrated region A₁ corresponding tothe first matching region 1032 in the matching region-based similarity1015. As illustrated in FIG. 10, a default value 0.0 may be allocated toanother or remaining region, for example, A₂. In an example, the defaultvalue 0.0 may have initially been allocated or set for all portions ofthe matching region-based similarity 1015, so after the updating of thefirst similarity 0.97 to the illustrated region A₁, the remainder of thematching region-based similarity 1015 may still have the default value0.0.

In one example, the fingerprint verification apparatus determines ascore based on the matching region-based similarity 1015, and thefingerprint verification apparatus then determines whether thefingerprint verification is successful based on whether the scoresatisfies a predetermined fingerprint verification condition. Thefingerprint verification condition may include, for example, arequirement that an average value of similarities in one or more regionsof the matching region-based similarity 1015, e.g., representing an areaequal to or greater than a set 80% of the entire matching region-basedsimilarity 1015 or the entire area of the input fingerprint image 1000,needs to be equal to or greater than a set 0.9. Such fingerprintverification condition requirements may be preset and/or updated by amanufacturer and/or set or selected by a user, such as by the userselecting from different levels or required similarities and areasbefore verification is considered a success.

In response to the score determined based on the matching region-basedsimilarity 1015 satisfying the fingerprint verification condition, thefingerprint verification apparatus determines that the fingerprintverification is successful and terminates the fingerprint verificationprocess without comparing the input fingerprint image 1000 to anotherregistered fingerprint image. Conversely, in response to the scoredetermined based on the matching region-based similarity 1015 notsatisfying the fingerprint verification condition, the fingerprintverification apparatus compares the input fingerprint image 1000 to asecond registered fingerprint image 1024, which is different from thefirst registered fingerprint image 1022, and determines a secondmatching region 1034 and a second similarity between the inputfingerprint image 1000 and the second registered fingerprint image 1024in operation 1040. In one example, the fingerprint verificationcondition may be determined based on of the size of the matchingregion(s), a similarity or similarities indicated in the matchingregion-based similarity 1015, or a combination of the size of thematching region(s) and the similarity or similarities indicated in thematching region-based similarity 1015.

With respect to determined second matching region and second similarity,the fingerprint verification apparatus updates the matching region-basedsimilarity 1015 based on the determined second matching region 1034 andthe determined second similarity. A reference numeral 1045 indicates avisualization of the matching region-based similarity that is updatedbased on the second matching region 1034 and the second similarity,after having been previously updated with respect to the first matchingregion 1032 and the first similarity. Here, in an example where thesecond similarity is determined to be 0.83, the fingerprint verificationapparatus thus allocates the second similarity 0.83 to the illustratedregion B₂ of a region corresponding to the second matching region 1034in the matching region-based similarity 1045. The illustrated region B₃of the corresponding region is a region matched to both the firstregistered fingerprint image 1022 and the second registered fingerprintimage 1024, and thus corresponds to an overlapping region between thefirst matching region 1032 and the second matching region 1034. In sucha case, the similarity corresponding to the region B₃ is determined tobe 0.97, which is the greater similarity between the previouslyallocated similarity 0.97 and the second similarity 0.83. For example,the similarity corresponding to the region B₃ may be maintained to bethe previously allocated 0.97, i.e., previously allocated based on thefirst similarity 0.97, without being updated based on the determinationthat the second similarity is less than the first similarity 0.97. Theexample default value 0.0 may be maintained for illustrated regions B₄and B₅, which have not yet been determined to correspond to matchingregions with any registered fingerprint image. The illustrated regionB₁, corresponding to the previously allocated first similarity 0.97 andthe first matching region 1032, is also maintained to have the allocated0.97 distinct from the allocated second similarity 0.83 allocated forthe second matching region 1034.

Similarly, in response to a score determined based on the matchingregion-based similarity 1045 not satisfying the fingerprint verificationcondition, the fingerprint verification apparatus compares the inputfingerprint image 1000 to a third registered fingerprint image 1026,determines a third matching region 1036 and a third similarity betweenthe input fingerprint image 1000 and the third registered fingerprintimage 1026, and updates the matching region-based similarity 1045 basedon the third matching region 1036 and the third similarity in operation1050. Here, the third similarity is determined to be 0.92. Theillustrated reference numeral 1055 is a visualization of this latestmatching region-based similarity that has been updated based on thethird matching region 1036 and the third similarity.

The fingerprint verification apparatus thus allocates the thirdsimilarity 0.92 to regions C₃, C₄, and C₅ of a region corresponding tothe third matching region 1036 in the matching region-based similarity1055. Previous allocated similarities corresponding to the regions C₃and C₄ were the example default 0.0, and thus are updated to be 0.92,which is a greater value than the default 0.0. The region C₅ is a regionthat is matched to both the second registered fingerprint image 1024 andthe third registered fingerprint image 1026, and thus corresponds to anoverlapping region between the second matching region 1034 and the thirdmatching region 1036. In such a case, a similarity corresponding to theregion C₅ is updated to be 0.92, which is the greater value between thepreviously allocated similarity 0.83 and the third similarity 0.92. Theexample default value 0.0 is thus maintained for the region C₆, whichhas not yet been determined to correspond to matching regions with anyregistered fingerprint image. The illustrated region C₁, correspondingto the previously allocated first similarity 0.97 and the first matchingregion 1032, is also maintained to have the allocated 0.97 distinct fromthe allocated third similarity 0.92 allocated for the third matchingregion 1036.

As described above, in a matching region-based similarity, respectivesimilarities between an input fingerprint image and each of theregistered fingerprint images may be determined with respect to eachmatching region between the input fingerprint image and each of theregistered fingerprint images. Further, each time the input fingerprintimage is compared to each of different registered fingerprint images anda corresponding additional matching region is determined, a totalmatching region of the matching region-based similarity may beincrementally expanded with each matching region-based similarityupdate.

Thus, when the updating of the matching region-based similarity 1045 iscompleted based on the third matching region 1036 and the thirdsimilarity, the fingerprint verification apparatus determines a scorebased on an updated matching region similarity 1055, and determineswhether the score satisfies the fingerprint verification condition. Inresponse to the score satisfying the fingerprint verification condition,the fingerprint verification apparatus determines that the fingerprintverification process of the input fingerprint image is successful andthe fingerprint verification apparatus may indicate the success of thefingerprint verification process. In response to the score notsatisfying the fingerprint verification condition, the fingerprintverification apparatus may sequentially perform the same operationsdescribed in the foregoing on each remaining registered fingerprintimages until the fingerprint verification condition is satisfied. Thefingerprint verification apparatus may determine that the fingerprintverification process is unsuccessful when a final score determined basedon a finally updated matching region-based similarity, e.g., obtained asa result of having performed such operations on all the registeredfingerprint images, does not satisfy the fingerprint verificationcondition.

FIGS. 11A and 11B are diagrams illustrating an example of a method ofperforming a fingerprint verification based on a matching region-basedsimilarity.

Referring to FIG. 11A, a matching region-based similarity 1120 may beembodied as an image having a same resolution as a resolution of aninput fingerprint image 1100. For example, in a case in which theresolution of the input fingerprint image 1100 is n×m, in which ndenotes a number of pixels in width and m denotes a number of pixels inlength, the resolution of the matching region-based similarity 1120 mayalso be n×m. Here, each of illustrated similarities included in thematching region-based similarity 1120 in FIG. 11A, for example,corresponds to a similarity between the input fingerprint image 1100 andeach of the multiple registered fingerprint images. As only an example,each of the registered fingerprint images may also have an n×mresolution.

Here, an input fingerprint image may be provided in the exampleillustrated rectangular shape, for example, the input fingerprint image1100 as illustrated in FIG. 11A, or in an oval shape, for example, aninput fingerprint image 1130 as illustrated in FIG. 11B. In one example,in a case in which an image of a fingerprint of a user is captured by afingerprint sensor, integrated in a display, while a finger of the useris touching the display, the resultant input fingerprint image 1130 inthe oval shape may be captured as illustrated in FIG. 11B. Alternativelyor additionally, a sensing region of the fingerprint sensor may have anoval shape, and the resultant input fingerprint image captured by thefingerprint sensor may have an oval shape. After the aforementionedoperations described above to respectively determine the matchingregion-based similarities of FIGS. 1-10, for example, the matchingregion-based similarity corresponding to such an oval-shaped inputfingerprint image, for example, the input fingerprint image 1130, may bevisualized as a matching region-based similarity 1140 illustrated inFIG. 11B, and the fingerprint verification determined based onconsiderations of the similarities and matching areas represented in thematching region-based similarity 1140, as also discussed above.

Referring back to FIG. 11A, and as an example, determining whether afingerprint verification condition is satisfied based on the matchingregion-based similarity 1120 will be described in greater detail below.

In the matching region-based similarity 1120, a first region 1122 is aregion associated with a matching region between the input fingerprintimage 1100 and a first registered fingerprint image, and 0.97 is thesimilarity allocated to the first region 1122. Similarities 0.83, 0.0,and 0.92 are similarity values allocated to a second region 1124, athird region 1126, and a fourth region 1128, respectively. Thesimilarity 0.0 may be a default value allocated to the third region 1126because the third region 1126 does not include a region matched to anyof all registered fingerprint images, or due to a determinedconsiderably low similarity to a registered fingerprint image resultingin such a matching region not being determined or resulting in adetermination to not adjust the default value because of theconsiderably low similarity, e.g., when the correspondingly determinedsimilarity fails to meet a predetermined minimum similarity.

In one example, the fingerprint verification apparatus determineswhether a fingerprint verification is successful based on whether a sizeof total of all matching regions, which have similarities that meet athreshold value (e.g., is greater than or equal to the threshold value),meets a threshold size (e.g., is greater than or equal to the thresholdsize) using the matching region-based similarity. For example, in a casein which the threshold value is 0.90 and the threshold size is A, forexample, 4000, the fingerprint verification apparatus determines thatthe first region 1122 and the fourth region 1128 are the only matchingregions whose similarities meet the threshold value, and then determinesthat the fingerprint verification is successful when a sum of a size ofthe first region 1122 and a size of the fourth region 1128 meets A. In acase of the matching region-based similarity 1120 is provided as animage, or representable by an image, the sum of the sizes may bedetermined to be the total number of pixels in the image to which asimilarity meeting 0.90 has been allocated.

In another example, the fingerprint verification apparatus determineswhether the fingerprint verification is successful based on whether anaverage value of the top or greatest value N similarities in thematching region-based similarity 1120 meets, e.g., is greater than orequal to, a threshold value. For example, in a case in which N is 100and the threshold value is 0.95, the fingerprint verification apparatusarranges or considers similarities in the matching region-basedsimilarity 1120 in a descending order and extracts the top 100similarities in order, and determines that the fingerprint verificationis successful when an average value of the extracted 100 similaritiesmeets, e.g., is greater than or equal to, a predetermined thresholdvalue of 0.95.

In still another example, the fingerprint verification apparatusdetermines whether the fingerprint verification is successful byarranging similarities in the matching region-based similarity 1120 in adescending order and determining whether a top M-th similarity isgreater than or equal to a threshold value. For example, in a case inwhich M is 200 and the threshold value is 0.9, the fingerprintverification apparatus arranges the similarities in the matchingregion-based similarity 1120 in a descending order, and determines thatthe fingerprint verification is successful when a top 200th similarityin the order of similarities meets, e.g., is greater than or equal to,0.9.

In these examples, values of N and M may be predetermined and/or set,adjusted, or updated by a manufacturer, service provider, and/or user,for example. Similarly, such thresholds herein may also bepredetermined, such as by a manufacturer, and/or set, adjusted, orupdated by the manufacturer, service provider, and/or user.

The fingerprint verification apparatus may determine whether thefingerprint verification is successful and/or may determine whether thefingerprint verification is unsuccessful using various fingerprintverification conditions, and a scope of examples is not limited by theexamples described in the foregoing.

FIG. 12 is a diagram illustrating an example of a fingerprintverification apparatus.

Referring to FIG. 12, a fingerprint sensor 1210 obtains, e.g., captures,reads, and/or receives, fingerprint information of a user, e.g., a userattempting at a fingerprint verification, and generates an inputfingerprint image. The input fingerprint image may be transferred ortransmitted to a fingerprint verification apparatus 1220, and thefingerprint verification apparatus 1220 is configured to perform thefingerprint verification by comparing the input fingerprint image to atleast one registered fingerprint image stored in a registered image DB1230. The verification process may further include a fingerprintregistration process, where the user may register fingerprint images ofeach of at least one finger, and the registered fingerprint image DB1230 may be generated and store the registered fingerprint images. Thefingerprint registration process may be performed by another fingerprintverification apparatus or another device that is connected to thefingerprint sensor 1210 or another fingerprint sensor for capturing oneor more fingerprints to generate and store the registered fingerprintimages. The registered fingerprint image DB 1230 may alternatively beincluded in the fingerprint verification apparatus 1220, just asexamples exist where the fingerprint sensor 1210 is included or separatefrom the fingerprint verification apparatus 1220. The fingerprintverification apparatus 1220 may respectively request or accessregistered fingerprint images from the registered fingerprint image DB1230, e.g., during the verification process, or the registeredfingerprint image DB 1230 may automatically provide the registeredfingerprint images to the fingerprint verification apparatus 1220 basedon a command of the fingerprint verification apparatus 1220. Here,though examples are presented for various embodiments, examples are notlimited thereto.

The fingerprint verification apparatus 1220 may be configured to performany one, combination, or all processes, stages, or operations of anyone, combination, or all fingerprint verification methods describedherein, such as discussed above with respect to FIGS. 1-11B, and providea result of the fingerprint verification to the user or another serveror device, such as through the aforementioned explicit or implicitindications of the results, as non-limiting examples. As a furtherexample, the fingerprint verification apparatus 1220 may provide anexample explicit indication of the result of the fingerprintverification through, for example, an output voice, vibration, displayedwritten character, displayed illustration, or displayed video. However,the indicating of the result is not limited to the examples described inthe foregoing, and the fingerprint verification apparatus 1220 mayindicate the result in various forms.

The fingerprint verification apparatus 1220 includes at least oneprocessor 1222 and a memory 1224. The memory 1224 is connected to theprocessor 1222, and stores instructions implementable by the processor1222, data to be operated by the processor 1222, and/or data processedby the processor 1222 for, during, or as a result of any, anycombination, or all of the fingerprint verification processes, stages,operations, and/or methods described herein. The memory 1224 mayinclude, for example, a non-transitory computer-readable medium, forexample, a high-speed random access memory and/or a nonvolatilecomputer-readable storage medium (e.g., at least one disk storagedevice, a flash memory device, and other nonvolatile solid-state memorydevices).

The processor 1222 executes such instructions to control the processor1222 to perform any one, combination, or all processes, stages,operations, and/or methods described with reference to FIGS. 1 through11B. Either through such executed instructions or through other hardwareimplementation, the processor 1222 may be configured to determine amatching region-based similarity based on a determined matching regionbetween the input fingerprint image and the at least one registeredfingerprint image, and determines a result of the fingerprintverification performed on the input fingerprint image based on thematching region-based similarity. The processor 1222 may be configuredto generate, set, or update the matching region-based similarity basedon the matching region between the input fingerprint image and theregistered fingerprint image and a similarity corresponding to thematching region between the input fingerprint image and the registeredfingerprint image. The processor 1222 determines whether the fingerprintverification is successful based on whether a score determined based onthe updated matching region-based similarity satisfies a fingerprintverification condition.

FIG. 13 is a diagram illustrating an example of a computing apparatus.

A computing apparatus 1300 performs a fingerprint verification processby obtaining a fingerprint image of a user and comparing the obtainedfingerprint image to a registered fingerprint image. The computingapparatus 1300 may be configured to include or implement thefunctionalities of the fingerprint verification apparatus 1220illustrated in FIG. 12, and thus the descriptions above are applicableto the operation of the computing apparatus 1300, and may not berepeated in full below merely for brevity purposes. In addition, in anexample, the computing apparatus 1300 corresponds to the fingerprintverification apparatus 1220. Referring to FIG. 13, the computingapparatus 1300 includes a processor 1310, a memory 1320, a fingerprintsensor 1330, a storage device 1340, an input device 1350, an outputdevice 1360, and a network interface 1370. The processor 1310 of thecomputing apparatus 1300, as well as the processor 1222 of FIG. 12, mayrespectively be representative of a single processor, multipleprocessors, or networked processors or computing devices that shareimplementations of operations between such processors. Thus, a referenceto a processor herein also refers to an example of one or moreprocessors. The processor 1310, the memory 1320, the fingerprint sensor1330, the storage device 1340, the input device 1350, the output device1360, and the network interface 1370 may further communicate with oneanother through an example communication bus 1380.

The processor 1310 is configured to implement functions and instructionsin the computing apparatus 1300. For example, the processor 1310 may beconfigured to execute instructions stored in the memory 1320 or thestorage device 1340. Thus, through such instructions and/or throughalternative hardware implementations, the processor 1310 is configuredto perform any one, combination, or all processes, stages, or operationsdescribed with reference to FIGS. 1 through 12.

The memory 1320 stores information to be used for the fingerprintverification process implemented by the computing apparatus 1300. Thememory 1320 includes a computer-readable storage medium or acomputer-readable storage device. For example, the memory 1320 includesa random access memory (RAM), a dynamic RAM (DRAM), a static RAM (SRAM),or nonvolatile memories in other forms in the technical field to whichthe present disclosure pertains after an understanding of the presentdisclosure. The memory 1320 may store the aforementioned instructions tobe implemented or executed by the processor 1310 and may store relatedinformation generated or relied upon during execution of any software orapplication being further implemented by the computing apparatus 1300.For example, the memory 1320 may store software or applications whoseexecution is indicative of success of the fingerprint verificationprocess, such as a mobile banking application or a process of the mobilebanking application being executed or authorized upon a successfulfingerprint verification.

The fingerprint sensor 1330 may obtain, e.g., capture, read, or receive,an input fingerprint image, e.g., in response to a detection ordetermination that a fingerprint is being input or provided from a user.The inputting of a fingerprint may include all actions or manipulationsperformed by the user from which the fingerprint may be obtained. Forexample, in a case in which a finger of the user comes into contact witha sensing region or the user performs a swipe motion on the sensingregion using a finger, the fingerprint sensor 1330 may be configured tosense the fingerprint of the user. In another example, in a case inwhich the fingerprint sensor 1330 is integrated in a display example, asurface of the display may be embodied as the sensing region and thefingerprint sensor 1330 may be configured to sense a fingerprint from afinger being determined to be in contact with the display. Thefingerprint sensor 1330 may be configured to perform various fingerprintinformation obtaining, e.g., capturing, reading, and/or receiving,methods, for example, an ultrasonic method, a mutual capacitance method,and an infrared image capturing method, as only examples. Thefingerprint sensor 1330 may capture, as a fingerprint image, afingerprint region corresponding to the sensing region of thefingerprint sensor 1330, for example.

The storage device 1340 includes a computer-readable storage medium or acomputer-readable storage device. The storage device 1340 stores a DBincluding registered fingerprint images. In one example, the storagedevice 1340 stores a greater amount of information than the memory 1320,and stores the information for a long period of time. For example, thestorage device 1340 may include, for example, a magnetic hard disk, anoptical disc, a flash memory, an erasable programmable read-only memory(EPROM), a floppy disk, and nonvolatile memories in other forms that arewell-known in the technical field to which the present disclosurepertains.

The input device 1350 is configured to obtain, e.g., capture, read,and/or receive, input from the user through a tactile, video, audio,and/or touch input. For example, the input device 1350 may include oneor more of a keyboard, a mouse, a touchscreen, a microphone, afingerprint reader, a retinal scanner, and other devices configured todetect an input from a user and transfer the detected input to thecomputing apparatus 1300.

The output device 1360 is configured to provide the user with an outputof the computing apparatus through a visual, auditory, and/or tactilechannel. For example, the output device 1360 may provide the user withthe output by visualizing information associated with a fingerprintverification. For example, the output device 1360 may include one ormore of a liquid crystal display (LCD), a light-emitting diode (LED)display, a touchscreen, a speaker, a vibration generator, and otherdevices configured to provide an output to the user.

The network interface 1370 may be configured to and/or controlled tocommunicate with an external device through a wired or wireless networkfor which the network interface 1370 is configured to interact with. Forexample, the network interface 1370 may include one or more of anEthernet card, an optical transceiver, a radio frequency transceiver,and other network interface cards configured to transmit and receiveinformation. The network interface 1370 may wirelessly communicate withthe external device through, for example, Bluetooth, WiFi, and a thirdgeneration (3G) or fourth generation (4G) communication method.

According to one or more example embodiments described herein, using amatching region-based similarity, a fingerprint verification may beperformed based on an integrated matching region and similarity betweenan input fingerprint image and each of various registered fingerprintimages. In addition, a false rejection and a false acceptance that mayoccur in the fingerprint verification when fingerprint image andregistered fingerprint images are independently compared without such amatching region-based similarity consideration may be prevented, andthus an accuracy in the fingerprint verification or a recognition ratemay be improved in an example.

The computing apparatus 100, fingerprint sensor 110, processors,fingerprint verification apparatuses, fingerprint sensor 1210,fingerprint verification apparatus 1220, processor 1222, memory 1224,processor 1310, memory 1320, computing apparatus 1300, fingerprintsensor 1330, storage device 1340, input device 1350, output device 1360,network interface 1370, and bus 1380, as only examples, and otherapparatuses, hardware modules, devices, and other components describedherein with respect to FIGS. 1-13 and that perform operations describedin this application are implemented by hardware components. Examples ofhardware components that may be used to perform the operations describedin this application where appropriate include controllers, sensors,generators, drivers, memories, comparators, arithmetic logic units,adders, subtractors, multipliers, dividers, integrators, and any otherelectronic components configured to perform the operations described inthis application. In other examples, one or more of the hardwarecomponents that perform the operations described in this application areimplemented by computing hardware, for example, by one or moreprocessors or computers. A processor or computer may be implemented byone or more processing elements, such as an array of logic gates, acontroller and an arithmetic logic unit, a digital signal processor, amicrocomputer, a programmable logic controller, a field-programmablegate array, a programmable logic array, a microprocessor, or any otherdevice or combination of devices that is configured to respond to andexecute instructions in a defined manner to achieve a desired result. Inone example, a processor or computer includes, or is connected to, oneor more memories storing instructions or software that are executed bythe processor or computer. Hardware components implemented by aprocessor or computer may execute instructions or software, such as anoperating system (OS) and one or more software applications that run onthe OS, to perform the operations described in this application. Thehardware components may also access, manipulate, process, create, andstore data in response to execution of the instructions or software. Forsimplicity, the singular term “processor” or “computer” may be used inthe description of the examples described in this application, but inother examples multiple processors or computers may be used, or aprocessor or computer may include multiple processing elements, ormultiple types of processing elements, or both. For example, a singlehardware component or two or more hardware components may be implementedby a single processor, or two or more processors, or a processor and acontroller. One or more hardware components may be implemented by one ormore processors, or a processor and a controller, and one or more otherhardware components may be implemented by one or more other processors,or another processor and another controller. One or more processors, ora processor and a controller, may implement a single hardware component,or two or more hardware components. A hardware component may have anyone or more of different processing configurations, examples of whichinclude a single processor, independent processors, parallel processors,single-instruction single-data (SISD) multiprocessing,single-instruction multiple-data (SIMD) multiprocessing,multiple-instruction single-data (MISD) multiprocessing, andmultiple-instruction multiple-data (MIMD) multiprocessing.

The processes and methods demonstrated in FIGS. 1-13 that perform theoperations described in this application are performed by computinghardware, for example, by one or more processors or computers,implemented as described above executing instructions or software toperform the operations described in this application that are performedby the methods. For example, a single operation or two or moreoperations may be performed by a single processor, or two or moreprocessors, or a processor and a controller. One or more operations maybe performed by one or more processors, or a processor and a controller,and one or more other operations may be performed by one or more otherprocessors, or another processor and another controller. One or moreprocessors, or a processor and a controller, may perform a singleoperation, or two or more operations.

Instructions or software to control a processor or computer to implementthe hardware components and perform the methods as described above arewritten as computer programs, code segments, instructions or anycombination thereof, for individually or collectively instructing orconfiguring the processor or computer to operate as a machine orspecial-purpose computer to perform the operations performed by thehardware components and the methods as described above. In one example,the instructions or software include machine code that is directlyexecuted by the processor or computer, such as machine code produced bya compiler. In another example, the instructions or software includehigher-level code that is executed by the processor or computer using aninterpreter. The instructions or software may be written using anyprogramming language based on the block diagrams and the flow chartsillustrated in the drawings and the corresponding descriptions in thespecification, which disclose algorithms for performing the operationsperformed by the hardware components and the methods as described above.

The instructions or software to control computing hardware, for example,one or more processors or computers, to implement the hardwarecomponents and perform the methods as described above, and anyassociated data, data files, and data structures, may be recorded,stored, or fixed in or on one or more non-transitory computer-readablestorage media. Examples of a non-transitory computer-readable storagemedium include read-only memory (ROM), random-access programmable readonly memory (PROM), electrically erasable programmable read-only memory(EEPROM), random-access memory (RAM), dynamic random access memory(DRAM), static random access memory (SRAM), flash memory, non-volatilememory, CD-ROMs, CD-Rs, CD+Rs, CD-RWs, CD+RWs, DVD-ROMs, DVD-Rs, DVD+Rs,DVD-RWs, DVD+RWs, DVD-RAMs, BD-ROMs, BD-Rs, BD-R LTHs, BD-REs, blue-rayor optical disk storage, hard disk drive (HDD), solid state drive (SSD),flash memory, a card type memory such as multimedia card micro or a card(for example, secure digital (SD) or extreme digital (XD)), magnetictapes, floppy disks, magneto-optical data storage devices, optical datastorage devices, hard disks, solid-state disks, and any other devicethat is configured to store the instructions or software and anyassociated data, data files, and data structures in a non-transitorymanner and provide the instructions or software and any associated data,data files, and data structures to one or more processors or computersso that the one or more processors or computers can execute theinstructions. In one example, the instructions or software and anyassociated data, data files, and data structures are distributed overnetwork-coupled computer systems so that the instructions and softwareand any associated data, data files, and data structures are stored,accessed, and executed in a distributed fashion by the one or moreprocessors or computers.

While this disclosure includes specific examples, it will be apparentafter an understanding of the disclosure of this application thatvarious changes in form and details may be made in these exampleswithout departing from the spirit and scope of the claims and theirequivalents. The examples described herein are to be considered in adescriptive sense only, and not for purposes of limitation. Descriptionsof features or aspects in each example are to be considered as beingapplicable to similar features or aspects in other examples. Suitableresults may be achieved if the described techniques are performed in adifferent order, and/or if components in a described system,architecture, device, or circuit are combined in a different manner,and/or replaced or supplemented by other components or theirequivalents. Therefore, the scope of the disclosure is defined not bythe detailed description, but by the claims and their equivalents, andall variations within the scope of the claims and their equivalents areto be construed as being included in the disclosure.

What is claimed is:
 1. A processor implemented fingerprint verificationmethod comprising: obtaining an input fingerprint image; determining amatching region between the input fingerprint image and a registeredfingerprint image; determining a similarity corresponding to thematching region, representing a determined indication of similaritiesbetween the input fingerprint image and the registered fingerprintimage; relating the determined similarity to the matching region asrepresented in a matching region-based similarity; determining a resultof a verification of the input fingerprint image based on the matchingregion-based similarity; and indicating the result of the verification.2. The method of claim 1, wherein the relating of the determinedsimilarity to the matching region as represented in the matchingregion-based similarity comprises: determining the matching region-basedsimilarity based on the matching region and the determined similarity.3. The method of claim 2, further comprising generating the matchingregion-based similarity to include default similarity values and withoutrepresenting a matching region, wherein the determining of the matchingregion-based similarity includes representing the matching region in thematching region-based similarity and changing, from the defaultsimilarity values, similarity values corresponding to the matchingregion represented in the matching region-based similarity to be thedetermined similarity.
 4. The method of claim 2, wherein the determiningof the result of the verification comprises: determining a score for thedetermined matching region-based similarity; and determining whether theverification is successful based on whether the score satisfies apredetermined fingerprint verification condition.
 5. The method of claim1, wherein the determining of the similarity corresponding to thematching region comprises determining a first similarity correspondingto a first matching region between the input fingerprint image and afirst registered fingerprint image, wherein the relating of thedetermined similarity to the matching region as represented in thematching region-based similarity comprises determining the matchingregion-based similarity based on the first similarity and the firstmatching region, and wherein, in response to a score determined based onthe determined matching region-based similarity not satisfying afingerprint verification condition, the fingerprint verification methodfurther comprises determining a second similarity corresponding to adetermined second matching region between the input fingerprint imageand a second registered fingerprint image.
 6. The method of claim 5,wherein the determining of the matching region-based similarity based onthe first similarity and the first matching region comprises allocatingthe first similarity to the first matching region as represented in thedetermined matching region-based similarity.
 7. The method of claim 5,wherein, in further response to the score determined based on thedetermined matching region-based similarity not satisfying thefingerprint verification condition, the fingerprint verification methodfurther comprises updating the determined matching region-basedsimilarity based on the second matching region and the secondsimilarity.
 8. The method of claim 7, wherein the updating of thedetermined matching region-based similarity based on the second matchingregion and the second similarity comprises: in response to anoverlapping region being present between the first matching region andthe second matching region, allocating or maintaining a greatestsimilarity between the first similarity and the second similarity to theoverlapping region as represented in the updated matching region-basedsimilarity.
 9. The method of claim 8, wherein the updating of thedetermined matching region-based similarity based on the second matchingregion and the second similarity further comprises: allocating thesecond similarity to a remaining region of the second matching region,in which the overlapping region is not reflected, as represented in theupdated matching region-based similarity.
 10. The method of claim 1,wherein the determining of the result of the verification comprises:determining a score for the matching region-based similarity; and inresponse to the score satisfying a predetermined fingerprintverification condition, determining that the verification of the inputfingerprint image is successful.
 11. The method of claim 10, wherein thedetermining of the result of the verification comprises: determiningwhether a total size of one or more matching regions, each havingsimilarities meeting a predetermined threshold value, meets apredetermined threshold size using a matching region-based similarityrepresenting plural matching regions with respect to plural registeredfingerprint images, and determining whether the verification of theinput fingerprint image is successful based on a result of thedetermining of whether the total size meets the predetermined thresholdsize.
 12. The method of claim 10, wherein the determining of the resultof the verification comprises: in response to an average similarityvalue, of similarity values respectively related to at least some ofplural matching regions represented in a matching region-basedsimilarity with respect to plural registered fingerprint images, meetinga predetermined threshold value, determining that the verification ofthe input fingerprint image is successful.
 13. The method of claim 12,wherein the at least some of the plural matching regions is less thanall of the plural matching regions represented in the matchingregion-based similarity.
 14. The method of claim 10, wherein thedetermining of the result of the verification further comprises: inresponse to a score determined based on the matching region-basedsimilarity determined with respect to all registered fingerprint imagesnot satisfying the predetermined fingerprint verification condition,determining that the verification of the input fingerprint image isunsuccessful.
 15. A non-transitory computer-readable medium storinginstructions, which when executed by a processor, cause the processor toperform the method of claim
 1. 16. A processor implemented fingerprintverification method comprising: obtaining an input fingerprint image;determining a first similarity corresponding to a first matching regionbetween the input fingerprint image and a first registered fingerprintimage; determining a matching region-based similarity based on the firstsimilarity and the first matching region; determining a score based onthe matching region-based similarity; in response to the score notsatisfying a predetermined fingerprint verification condition:determining a second similarity corresponding to a second matchingregion between the input fingerprint image and a second registeredfingerprint image; and updating the matching region-based similaritybased on the second similarity and the second matching region; anddetermining a result of a verification of the input fingerprint imagebased on the matching region-based similarity or the updated matchingregion-based similarity.
 17. The method of claim 16, wherein theupdating of the matching region-based similarity comprises: in responseto an overlapping region being present between the first matching regionand the second matching region, allocating or maintaining a greatestsimilarity between the first similarity and the second similarity to theoverlapping region represented in the updated matching region-basedsimilarity.
 18. The method of claim 17, wherein the updating of thematching region-based similarity further comprises: allocating thesecond similarity to a remaining region, of the second matching regionin which the overlapping region is not reflected, as represented in theupdated the updated matching region-based similarity.
 19. The method ofclaim 16, wherein the determining of the result of the verificationcomprises: determining whether a total size of one or more matchingregions, each having a similarity meeting a predetermined thresholdvalue, meets a predetermined threshold size using a matchingregion-based similarity representing plural matching regions withrespect to plural registered fingerprint images including the firstregistered fingerprint image and the second registered fingerprintimage, and determining whether the verification of the input fingerprintimage is successful based on a result of the determining of whether thetotal size meets the predetermined threshold size.
 20. The method ofclaim 16, wherein the determining of the result of the verificationcomprises: in response to an similarity average value, of similarityvalues respectively related to at least some of plural matching regionsrepresented in a matching region-based similarity with respect to pluralregistered fingerprint images including the first registered fingerprintimage and the second registered fingerprint image, meeting apredetermined threshold value, determining that the verification of theinput fingerprint image is successful.
 21. A processor implementedfingerprint verification method comprising: obtaining an inputfingerprint image; determining a first matching region between the inputfingerprint image and a first registered fingerprint image; determininga first similarity corresponding to the first matching region;determining a matching region-based similarity based on the firstsimilarity and the first matching region; determining a second matchingregion between the input fingerprint image and a second registeredfingerprint image; determining a second similarity corresponding to thesecond matching region; updating the matching region-based similaritybased on the second similarity and the second matching region;determining a score based on a finally updated matching region-basedsimilarity representing plural matching regions with respect to pluralregistered fingerprint images including the first registered fingerprintimage and the second registered fingerprint image; and determining aresult of a verification of the input fingerprint image based whether onthe score meets a predetermined verification condition.
 22. The methodof claim 21, wherein the updating of the matching region-basedsimilarity comprises: in response to an overlapping region being presentbetween the first matching region and the second matching region,allocating or maintaining a greatest similarity, between the firstsimilarity corresponding to the first matching region and the secondsimilarity corresponding to the second matching region, to theoverlapping region represented in the updated matching region-basedsimilarity.
 23. The method of claim 22, wherein the updating of thematching region-based similarity further comprises: allocating thesecond similarity to a remaining region, of the second matching regionin which the overlapping region is not reflected, as represented in theupdated matching region-based similarity.
 24. The method of claim 21,wherein the determining of the result of the verification comprises:determining whether a total size of one or more matching regions, eachhaving a similarity meeting a predetermined threshold value, meets apredetermined threshold size using the finally updated matchingregion-based similarity, and determining whether the verification of theinput fingerprint image is successful based on a result of thedetermining of whether the total size meets the predetermined thresholdsize.
 25. The method of claim 21, wherein the determining of the resultof the verification comprises: in response to a similarity averagevalue, of similarity values respectively related to at least some of theplural matching regions represented in the finally updated matchingregion-based similarity, meeting a predetermined threshold value,determining that the verification of the input fingerprint image issuccessful.
 26. A processor implemented fingerprint verification methodcomprising: obtaining an input fingerprint image; incrementally updatinga matching region-based similarity respectively based on determinedsimilarities for respectively determined matching regions between theinput fingerprint image and each of plural registered fingerprintimages; determining respective scores with respect to each of one ormore of the incremental updatings of the matching region-basedsimilarity, or a final score based on a finally updated matchingregion-based similarity representing plural matching regions withrespect to at least a multiple of the plural registered fingerprintimages; determining a result of a verification of the input fingerprintimage based whether any of the respective scores or the final scoremeets a predetermined verification condition; and indicating thedetermined result of the verification.
 27. The method of claim 26,wherein the determining of the respective scores with respect to each ofone or more of the incremental updatings of the matching region-basedsimilarity ceases when a corresponding score, of the respective scores,is determined in the determining of the result of the verification asmeeting the predetermined verification condition.
 28. A fingerprintverification apparatus comprising: a processor configured to: determinea matching region between an input fingerprint image and a registeredfingerprint image; determine a similarity corresponding to the matchingregion, representing a determined indication of similarities between theinput fingerprint image and the registered fingerprint image; relate thedetermined similarity to the matching region as represented in amatching region-based similarity; determine a result of a verificationof the input fingerprint image based on the matching region-basedsimilarity; and indicate the result of the verification.
 29. Thefingerprint verification apparatus of claim 28, wherein the processor isfurther configured to determine the matching region-based similaritybased on the matching region between the input fingerprint image and theregistered fingerprint image and the similarity corresponding to thematching region between the input fingerprint image and the registeredfingerprint image.
 30. The fingerprint verification apparatus of claim29, wherein the processor is further configured to determine a scorebased on the updated matching region-based similarity, and determine theresult of the verification based on whether the score satisfies apredetermined fingerprint verification condition.